Join the ACI Learning Adventure!

Our Mission

Welcome to a new era of learning, where individuals and organizations come to transform goals into measurable success. At ACI Learning, we believe that anything worth doing is worth leading the way—with innovation, exceptional experiences, and impactful results.

We provide a full ecosystem of learning and development solutions that empower people and businesses to lead with confidence, learn with purpose, and achieve outcomes that matter. Join us, and together, we'll shape the future of skill-building and professional growth.

The ACI Team

Imagine collaborating with over 200 of the brightest minds who are passionate, grounded, and dedicated to shaping the future of eLearning. Together, we're not just a team; we're a movement in one of the most exciting times in tech.

Purpose-Driven Culture

At ACI Learning, work isn’t just a job. It’s a passion we pour into every project, every day. We celebrate creativity, innovation, and the joy of doing what we love.

Your Opportunity

Are you ready to be part of something transformative? Dive into a world of collaboration, growth, and endless potential. Apply now and help lead the change!

 

Who We Are

ACI Learning is a leading provider of audit, cybersecurity and IT training solutions, empowering individuals and organizations worldwide to improve their technical capabilities and their cybersecurity with compelling and comprehensive training. Our leadership position extends even further to our new SaaS Learning Platform myACI that goes beyond audit, cyber and IT training to provide organizational and individual knowledge assessment, analytics and training delivery with integrated AI to understand capabilities and skill gaps for organizations.

Technical Instructor I

Part-Time | Onsite | ACI Tech Academy (San Antonio)

Teach the skills that launch careers in IT.

At ACI Learning, our mission is to transform lives through technical education. Our Technical Instructors play a critical role in helping learners build the technical skills, confidence, and certifications needed to start careers in IT and cybersecurity.

As a Technical Instructor I, you’ll deliver hands-on training that prepares learners for industry-recognized certifications and real-world technical roles. You’ll guide students through structured coursework, facilitate labs that reinforce practical skills, and support learners as they prepare for certification exams and entry into the technology workforce.

This role is ideal for technologists who enjoy sharing their expertise, mentoring learners, and helping others break into the IT field.

What You’ll Do

Instruction & Classroom Delivery

• Deliver engaging IT training in classroom, virtual, and webinar-based environments
• Teach established curriculum aligned to industry certifications and workforce needs
• Facilitate interactive discussions and hands-on activities that reinforce technical concepts
• Create a positive learning environment that encourages participation and skill development

Hands-On Learning & Certification Preparation

• Lead virtual and in-person lab activities to help learners build real-world technical skills
• Facilitate structured study sessions designed to reinforce learning and exam readiness
• Coach learners through certification preparation and support them toward successful exam completion
• Align instruction with evolving IT industry standards and job market requirements

Student Support & Engagement

• Provide academic support through mentoring, coaching, and informal assistance (including floor support and troubleshooting guidance)
• Monitor learner progress and proactively support students who need additional guidance
• Encourage consistent engagement and accountability throughout the training program

Training Environment & Collaboration

• Prepare and maintain classroom and lab environments, including IT equipment and learning systems
• Maintain accurate records of instructional activity and learner progress
• Collaborate with fellow instructors to ensure consistent, high-quality training delivery across programs

What Success Looks Like

• Learners stay engaged and successfully complete training programs
• Students build confidence through hands-on technical experience
• Graduates achieve industry-recognized certifications and enter the IT workforce
• Training delivery remains consistent, high-quality, and aligned with industry expectations

Minimum Qualifications

• 3+ years of instructional or technical teaching experience
• At least one active certification in CompTIA A+, Network+, or Security+
• Additional certifications aligned with the program may be required within 60 days of hire
• Ability to effectively deliver established curriculum and training materials
• Demonstrated classroom management and learner engagement skills

Preferred Qualifications

• Bachelor’s degree in a related field from an accredited institution
• Additional industry-recognized technical certifications
• Experience supporting certification exam preparation and learner success initiatives
• Familiarity with workforce-aligned, certification-based training programs
• Experience working with adult learners or individuals transitioning into technology careers

Skills That Set You Apart

• Strong technical expertise within the IT domain being taught
• Ability to explain complex technical concepts in a clear and accessible way
• Passion for helping learners build confidence and technical capability
• Strong communication and classroom facilitation skills
• Ability to maintain a structured, engaging, and supportive learning environment
• Professional reliability and consistent on-site presence

Why ACI Learning is Your Next Big Move

For Full-Time, Benefits Eligible Positions

Comprehensive medical, dental, and vision coverage—starting the 1st of the month after your hire date.

Four weeks of paid parental or medical leave, so you can focus on what matters most.

Flexible PTO policy, sick time, and eight paid holidays — because we believe in balance.

401(k) retirement plan with immediate vesting and up to 5% matching contributions — we invest in your future from day one.

One free course each year after 90 days — advancing your skills is part of the job.

Tuition assistance to support your continued education and professional growth.

At Texas Chiller Systems (TCS) we focus on excellence and teamwork across HVAC, plumbing, and electrical trades. We support commercial properties with strong maintenance, repair, and installation services. The Account Executive (AE) is the face of Texas Chiller Systems who develops, expands, and protects long-term customer relationships across commercial, industrial, institutional, and mission-critical environments.

This role blends strategic hunting, relationship-driven consulting, and technical solutioning across HVAC service, retrofit, and small-to-mid-size project opportunities. Your mission: grow profitable owner-direct business, deepen existing accounts, and elevate TCS’s reputation for reliability and excellence.

Key Responsibilities:

• Drive new owner-direct business development through prospecting, territory mapping, and consistent outreach.
• Build and maintain strong customer relationships with building owners, facility managers, property teams, and industrial operators.
• Manage and grow a personal book of business, focusing on renewals, expansion, and customer retention.
• Conduct site visits, assessments, and discovery to identify service, maintenance, and retrofit needs.
• Develop scopes and collaborate with Operations/Estimating to ensure accurate pricing and feasibility.
• Prepare and deliver compelling proposals for maintenance agreements, equipment replacements, upgrades, and retrofit projects.
• Maintain disciplined CRM usage including activity tracking, forecasting, deal probability, and pipeline updates.
• Follow up on technician-identified service opportunities and ensure timely engagement with customers.
• Partner cross-functionally with Service, Project Management, Estimating, and Purchasing to ensure seamless execution.
• Stay active in the market through industry events, networking, and competitive research

Qualifications: 

• 3–7+ years of successful outside B2B sales experience in commercial HVAC, mechanical services, building services, or related technical industries.
• Proven track record of meeting or exceeding sales quotas.
• Strong relationship-building and consultative selling skills.
• Ability to understand mechanical systems and translate technical concepts into value-focused business conversations.
• High discipline in CRM usage, pipeline management, and forecasting.
• Strong communication, negotiation, and presentation skills.
• Valid driver’s license and willingness to travel within territory and between TCS branch locations.

Why work here:

• High-Growth Market Opportunity - Texas is booming, and TCS is expanding aggressively with enormous untapped owner-direct potential.
• Strong Technical Backbone - You’ll sell with confidence knowing you have deep bench strength in Service, Projects, Estimating, and field expertise that consistently delivers.
• Competitive Compensation Structure - A strong base + incentive model tied directly to profitable growth. Uncapped commissions equal unlimited earning potential.
• Autonomy with Support - You’ll run your market with independence while having true operational alignment behind you.
• A Culture That Values Relationships - Internally and externally. Customers stay with people they trust, and TCS invests in building long-term partnerships, not transactional wins.

Job Type: Full-time, In-person. Monday through Friday, standard business hours, with flexibility for client needs and site visits.

Schedule: 

• 7:00 am - 6:00 pm availability 
• Monday to Friday 
• May be required to come in early or stay late to accommodate special opportunities.  

Texas Chiller Systems is an equal opportunity employer that is committed to providing all employees with a work environment free of discrimination and harassment. We celebrate diversity and welcome applicants from every background and life experience.  

Disclaimer: The above statements are intended to describe the general nature and level of work being performed by persons assigned to this job.  These statements are not to be translated as an exhaustive list of all responsibilities, duties, and skills required of personnel in this position.  All team members may be required to perform duties outside of their normal responsibilities from time to time as needed. 

Why This Role Matters 

As the first point of contact for our potential and current clients, you play a critical role in shaping the client experience. You’ll ensure consultations are scheduled efficiently, communications are handled with care, and attorney calendars run smoothly helping clients feel supported from their very first interaction. This role also contributes directly to new client conversion and retention with bonus opportunities tied to performance.  

What You’ll Do

•    Serve as the primary point of contact for incoming client inquiries 
•    Schedule, confirm, and reschedule consultations 
•    Manage attorney calendars to maximize efficiency 
•    Conduct timely follow-up with prospective clients 
•    Deliver a professional, empathetic intake experience 
•    Enter and maintain accurate client data in our Case Management System
•    Monitor and respond to calls, emails, and voicemails promptly 
•    Maintain an organized office and reception space 
•    Coordinate couriers, process servers, and marketing materials 
•    Process deposits, invoices, and check requests 
•    Handle sensitive client information with discretion and care 

What We’re Looking For

We’re looking for someone who brings a blend of professionalism, reliability, and a commitment to quality client service. Ideal candidates will possess:

•    High school diploma or GED 
•    Experience in a law office, medical office, or professional setting preferred 
•    Strong communication and client service skills 
•    Highly organized with strong attention to detail 
•    Ability to multitask and manage competing priorities 
•    Proficiency in Microsoft Office (Word, Outlook, Excel) 
•    Professional presence and dependable attendance (on-site, M–F, 8–5) 
•    Proactive, solutions-oriented mindset 
 
Acknowledgement:
The above statements describe the job’s essential responsibilities and requirements. They are not an exhaustive list of the duties that may be assigned to job incumbents.

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Overview

Join us to work collaboratively with our talented team of dynamic and passionate engineers to deliver capabilities that enable our customers to make a difference. You'll deploy and operate ArcGIS Velocity and ArcGIS Workflow Manager SaaS solutions. You will also have the opportunity to design, deploy, and operate next-generation real-time and big data GIS software-as-a-service (SaaS) capabilities for thousands of cloud users worldwide.

Our teams have a broad mix of experience levels and tenures that support an environment which promotes professional development. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Our team also puts a high value on work-life balance, and we understand that striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We offer a flexible hybrid schedule so you can have a more productive and well-balanced life both in and outside of work.

The Professional Services division is the consulting and implementation arm of Esri. We break ground in new markets, push the technology envelope and ultimately deliver transformational solutions to high profile clients worldwide. The Professional Services organization is comprised of nearly 1,000 talented business and technical professionals who strive every day to help our users be successful. This product team works closely with solution delivery consultants to envision and then ‘make real’ the emerging requirements in industry, government, and other user communities.

Responsibilities

• Collaborate with a team of SRE engineers to operate SaaS capabilities across multiple regions on the cloud platform
• Design, implement, configure, and utilize monitoring systems to monitor the health of SaaS products
• Manage infrastructure used for ArcGIS Velocity and ArcGIS Workflow Manager, respond to alerts, and troubleshoot problems to resolution
• Develop, implement, and maintain automation solutions for repetitive operational tasks, such as deployment pipelines, incident resolution, and scaling processes
• Design and implement the deployment and upgrade containerized micro-service components that, when combined, power Esri’s SaaS offerings
• Create and automate Git workflows to simplify code integration, testing, and infrastructure deployments
• Participate in technical spike efforts, bringing new innovative ideas to future versions of our software
• Troubleshoot the system incidents and provide root cause analysis reports
• Provide rotational on-call technical support

Requirements

• 5+ years of experience managing Kubernetes (EKS), logging and monitoring (ELK, Prometheus), and container technologies (Docker, ECS)
• Proficient in using Terraform for automating infrastructure provisioning and management
• Ability to design and automate Git workflows for streamlined code integration, testing, and infrastructure deployment
• Ability to write scripts to deploy infrastructure and/or applications (Bash, Python, Terraform)
• High level of understanding and experience with cloud computing platforms (AWS)
• Strong knowledge of Linux Operating system administration, including troubleshooting, performance tuning, and shell scripting
• Proficient in cloud networking, including VPCs, subnets, security groups, and VPNs in platforms like AWS
• Skilled in identifying and resolving system and application issues through effective troubleshooting and root cause analysis
• Working knowledge of a source control and issue management system, preferably GitHub
• Working knowledge of authoring, deploying, and troubleshooting Java applications on AWS Lambda
• Bachelor’s degree in computer science, computer engineering, GIS, or information systems

Recommended Qualifications

• 5+ years of experience designing, administering, and/or maintaining cloud environments, such as AWS, supporting 24×7 high-availability production environments
• Interest in working with GitOps principles to automate the deployment of applications on Kubernetes clusters
• Certifications: AWS Certified Solution Architect Associate, CKA/CKAD or similar
• Experience managing OpenSearch (datastore or logstore), and Kafka for managing distributed data streams and ensuring high availability in large-scale systems
• Ability to work with continuous integration and delivery best practices
• Knowledge of operating resilient, highly available, scalable, and performance SaaS capabilities
• Knowledge of Esri ArcGIS or other web mapping technologies
• Master’s degree in computer science, computer engineering, GIS, or information systems

#LI-DR5

Overview

Join us to work collaboratively with our talented team of dynamic and passionate engineers to deliver capabilities that enable our customers to make a difference. You'll deploy and operate ArcGIS Velocity and ArcGIS Workflow Manager SaaS solutions. You will also have the opportunity to design, deploy, and operate next-generation real-time and big data GIS software-as-a-service (SaaS) capabilities for thousands of cloud users worldwide.

Our teams have a broad mix of experience levels and tenures that support an environment which promotes professional development. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Our team also puts a high value on work-life balance, and we understand that striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We offer a flexible hybrid schedule so you can have a more productive and well-balanced life both in and outside of work.

The Professional Services division is the consulting and implementation arm of Esri. We break ground in new markets, push the technology envelope and ultimately deliver transformational solutions to high profile clients worldwide. The Professional Services organization is comprised of nearly 1,000 talented business and technical professionals who strive every day to help our users be successful. This product team works closely with solution delivery consultants to envision and then ‘make real’ the emerging requirements in industry, government, and other user communities.

Responsibilities

• Collaborate with a team of SRE engineers to operate SaaS capabilities across multiple regions on the cloud platform
• Design, implement, configure, and utilize monitoring systems to monitor the health of SaaS products
• Manage infrastructure used for ArcGIS Velocity and ArcGIS Workflow Manager, respond to alerts, and troubleshoot problems to resolution
• Develop, implement, and maintain automation solutions for repetitive operational tasks, such as deployment pipelines, incident resolution, and scaling processes
• Design and implement the deployment and upgrade containerized micro-service components that, when combined, power Esri’s SaaS offerings
• Create and automate Git workflows to simplify code integration, testing, and infrastructure deployments
• Participate in technical spike efforts, bringing new innovative ideas to future versions of our software
• Troubleshoot the system incidents and provide root cause analysis reports
• Provide rotational on-call technical support

Requirements

• 5+ years of experience managing Kubernetes (EKS), logging and monitoring (ELK, Prometheus), and container technologies (Docker, ECS)
• Proficient in using Terraform for automating infrastructure provisioning and management
• Ability to design and automate Git workflows for streamlined code integration, testing, and infrastructure deployment
• Ability to write scripts to deploy infrastructure and/or applications (Bash, Python, Terraform)
• High level of understanding and experience with cloud computing platforms (AWS)
• Strong knowledge of Linux Operating system administration, including troubleshooting, performance tuning, and shell scripting
• Proficient in cloud networking, including VPCs, subnets, security groups, and VPNs in platforms like AWS
• Skilled in identifying and resolving system and application issues through effective troubleshooting and root cause analysis
• Working knowledge of a source control and issue management system, preferably GitHub
• Working knowledge of authoring, deploying, and troubleshooting Java applications on AWS Lambda
• Bachelor’s degree in computer science, computer engineering, GIS, or information systems

Recommended Qualifications

• 5+ years of experience designing, administering, and/or maintaining cloud environments, such as AWS, supporting 24×7 high-availability production environments
• Interest in working with GitOps principles to automate the deployment of applications on Kubernetes clusters
• Certifications: AWS Certified Solution Architect Associate, CKA/CKAD or similar
• Experience managing OpenSearch (datastore or logstore), and Kafka for managing distributed data streams and ensuring high availability in large-scale systems
• Ability to work with continuous integration and delivery best practices
• Knowledge of operating resilient, highly available, scalable, and performance SaaS capabilities
• Knowledge of Esri ArcGIS or other web mapping technologies
• Master’s degree in computer science, computer engineering, GIS, or information systems

#LI-DR5

Overview

Join us to work collaboratively with our talented team of dynamic and passionate engineers to deliver capabilities that enable our customers to make a difference. You'll deploy and operate ArcGIS Velocity and ArcGIS Workflow Manager SaaS solutions. You will also have the opportunity to design, deploy, and operate next-generation real-time and big data GIS software-as-a-service (SaaS) capabilities for thousands of cloud users worldwide.

Our teams have a broad mix of experience levels and tenures that support an environment which promotes professional development. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Our team also puts a high value on work-life balance, and we understand that striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We offer a flexible hybrid schedule so you can have a more productive and well-balanced life both in and outside of work.

The Professional Services division is the consulting and implementation arm of Esri. We break ground in new markets, push the technology envelope and ultimately deliver transformational solutions to high profile clients worldwide. The Professional Services organization is comprised of nearly 1,000 talented business and technical professionals who strive every day to help our users be successful. This product team works closely with solution delivery consultants to envision and then ‘make real’ the emerging requirements in industry, government, and other user communities.

Responsibilities

• Collaborate with a team of SRE engineers to operate SaaS capabilities across multiple regions on the cloud platform
• Design, implement, configure, and utilize monitoring systems to monitor the health of SaaS products
• Manage infrastructure used for ArcGIS Velocity and ArcGIS Workflow Manager, respond to alerts, and troubleshoot problems to resolution
• Develop, implement, and maintain automation solutions for repetitive operational tasks, such as deployment pipelines, incident resolution, and scaling processes
• Design and implement the deployment and upgrade containerized micro-service components that, when combined, power Esri’s SaaS offerings
• Create and automate Git workflows to simplify code integration, testing, and infrastructure deployments
• Participate in technical spike efforts, bringing new innovative ideas to future versions of our software
• Troubleshoot the system incidents and provide root cause analysis reports
• Provide rotational on-call technical support

Requirements

• 5+ years of experience managing Kubernetes (EKS), logging and monitoring (ELK, Prometheus), and container technologies (Docker, ECS)
• Proficient in using Terraform for automating infrastructure provisioning and management
• Ability to design and automate Git workflows for streamlined code integration, testing, and infrastructure deployment
• Ability to write scripts to deploy infrastructure and/or applications (Bash, Python, Terraform)
• High level of understanding and experience with cloud computing platforms (AWS)
• Strong knowledge of Linux Operating system administration, including troubleshooting, performance tuning, and shell scripting
• Proficient in cloud networking, including VPCs, subnets, security groups, and VPNs in platforms like AWS
• Skilled in identifying and resolving system and application issues through effective troubleshooting and root cause analysis
• Working knowledge of a source control and issue management system, preferably GitHub
• Working knowledge of authoring, deploying, and troubleshooting Java applications on AWS Lambda
• Bachelor’s degree in computer science, computer engineering, GIS, or information systems

Recommended Qualifications

• 5+ years of experience designing, administering, and/or maintaining cloud environments, such as AWS, supporting 24×7 high-availability production environments
• Interest in working with GitOps principles to automate the deployment of applications on Kubernetes clusters
• Certifications: AWS Certified Solution Architect Associate, CKA/CKAD or similar
• Experience managing OpenSearch (datastore or logstore), and Kafka for managing distributed data streams and ensuring high availability in large-scale systems
• Ability to work with continuous integration and delivery best practices
• Knowledge of operating resilient, highly available, scalable, and performance SaaS capabilities
• Knowledge of Esri ArcGIS or other web mapping technologies
• Master’s degree in computer science, computer engineering, GIS, or information systems

#LI-DR5

Overview

Join us to work collaboratively with our talented team of dynamic and passionate engineers to deliver capabilities that enable our customers to make a difference. You'll deploy and operate ArcGIS Velocity and ArcGIS Workflow Manager SaaS solutions. You will also have the opportunity to design, deploy, and operate next-generation real-time and big data GIS software-as-a-service (SaaS) capabilities for thousands of cloud users worldwide.

Our teams have a broad mix of experience levels and tenures that support an environment which promotes professional development. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Our team also puts a high value on work-life balance, and we understand that striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We offer a flexible hybrid schedule so you can have a more productive and well-balanced life both in and outside of work.

The Professional Services division is the consulting and implementation arm of Esri. We break ground in new markets, push the technology envelope and ultimately deliver transformational solutions to high profile clients worldwide. The Professional Services organization is comprised of nearly 1,000 talented business and technical professionals who strive every day to help our users be successful. This product team works closely with solution delivery consultants to envision and then ‘make real’ the emerging requirements in industry, government, and other user communities.

Responsibilities

• Collaborate with a team of SRE engineers to operate SaaS capabilities across multiple regions on the cloud platform
• Design, implement, configure, and utilize monitoring systems to monitor the health of SaaS products
• Manage infrastructure used for ArcGIS Velocity and ArcGIS Workflow Manager, respond to alerts, and troubleshoot problems to resolution
• Develop, implement, and maintain automation solutions for repetitive operational tasks, such as deployment pipelines, incident resolution, and scaling processes
• Design and implement the deployment and upgrade containerized micro-service components that, when combined, power Esri’s SaaS offerings
• Create and automate Git workflows to simplify code integration, testing, and infrastructure deployments
• Participate in technical spike efforts, bringing new innovative ideas to future versions of our software
• Troubleshoot the system incidents and provide root cause analysis reports
• Provide rotational on-call technical support

Requirements

• 5+ years of experience managing Kubernetes (EKS), logging and monitoring (ELK, Prometheus), and container technologies (Docker, ECS)
• Proficient in using Terraform for automating infrastructure provisioning and management
• Ability to design and automate Git workflows for streamlined code integration, testing, and infrastructure deployment
• Ability to write scripts to deploy infrastructure and/or applications (Bash, Python, Terraform)
• High level of understanding and experience with cloud computing platforms (AWS)
• Strong knowledge of Linux Operating system administration, including troubleshooting, performance tuning, and shell scripting
• Proficient in cloud networking, including VPCs, subnets, security groups, and VPNs in platforms like AWS
• Skilled in identifying and resolving system and application issues through effective troubleshooting and root cause analysis
• Working knowledge of a source control and issue management system, preferably GitHub
• Working knowledge of authoring, deploying, and troubleshooting Java applications on AWS Lambda
• Bachelor’s degree in computer science, computer engineering, GIS, or information systems

Recommended Qualifications

• 5+ years of experience designing, administering, and/or maintaining cloud environments, such as AWS, supporting 24×7 high-availability production environments
• Interest in working with GitOps principles to automate the deployment of applications on Kubernetes clusters
• Certifications: AWS Certified Solution Architect Associate, CKA/CKAD or similar
• Experience managing OpenSearch (datastore or logstore), and Kafka for managing distributed data streams and ensuring high availability in large-scale systems
• Ability to work with continuous integration and delivery best practices
• Knowledge of operating resilient, highly available, scalable, and performance SaaS capabilities
• Knowledge of Esri ArcGIS or other web mapping technologies
• Master’s degree in computer science, computer engineering, GIS, or information systems

#LI-DR5

Description

Captivation Software is seeking a highly motivated and experienced DevOps Engineer to join our fast-paced development team. The ideal candidate will have strong working knowledge in Linux systems administration, and a background in Big Data solutions, configuration management, automation, scripting, and AWS. The DevOps Engineer will be responsible for implementing infrastructure, automating deployment processes, and ensuring the reliability and scalability of our services. Work is performed mostly on customer site in San Antonio, TX 5 days/week. 

If you have a passion for DevOps and are interested in working with a dynamic and innovative team, we encourage you to apply for this exciting opportunity.

Responsibilities

• Support development and deployment of cloud infrastructure in AWS
• Support development and deployment of non-cloud (Edge) infrastructure of on-premise and portable equipment
• Automate deployment processes and ensure reliability and scalability of services
• Manage and maintain Kubernetes containers and cloud infrastructure on AWS
• Collaborate with development teams to integrate their applications into the infrastructure
• Monitor and troubleshoot production systems and resolve issues as necessary
• Continuously improve processes and tools to ensure high availability and performance
• Stay current with new technologies and industry trends, continuously exploring new ways to improve our infrastructure
• Other duties as assigned

Requirements

Security Clearance:

• A current TS/SCI U.S. Government Security clearance is required; U.S. citizenship required. 

Minimum Qualifications:

• 5+ years of experience in DevOps Engineering or Software Development (Java preferred) and Bachelors in related field; or 3 years relevant experience with Masters in related field; or High School Diploma or equivalent and 9 years relevant experience.
• Strong knowledge of Linux, including system administration and troubleshooting
• Proficient in configuration management tools such as Ansible or Puppet
• Knowledge of AWS services (EC2, S3, Lambda) and their application to deployment and management of infrastructure
• Experience with application and OS deployment, scaling, and management
• Ability to develop in multiple programming languages such as bash, Python, or Go
• Familiarity with Git and other development tools such as deployment pipelines
• Excellent problem-solving skills and the ability to identify and troubleshoot complex issues
• Excellent oral and written communication skills.
• Understanding of AGILE software development methodologies and use of standard software development tool suites
• Must be able to obtain Security+ certification within 60 days of hire.
• Must be able to work on-site daily at the customer location in San Antonio, TX, with occasional opportunities to be working from home. Flexibility is essential to accommodate schedule changes based on customer and team needs.

Preferred Qualifications:

• Experience with big data technologies like: Hadoop, Spark, PostgreSQL, ElasticSearch, Hive, Drill, Impala, Trino, Presto, etc.
• Experience with containers EKS, Diode, CI/CD, and Terraform are a plus
• Work could possibly require some on-call work. 

This position is open for direct hires only. We will not consider candidates from third party staffing/recruiting firms.